NDLI: Channel order and RMS delay spread estimation for AC power line communications

Content Provider	IEEE Xplore Digital Library
Author	Hongbin Li Zhaoqiang Bi Duixian Liu Jian Li Stoica, P.
Copyright Year	2000
Description	Author affiliation: Dept. of ECE, Stevens Inst. of Technol., Hoboken, NJ, USA (Hongbin Li)
Abstract	AC power lines have been considered as a convenient and low-cost medium for intra-building automation systems. We investigate the problem of estimating the channel order and root mean squared (RMS) delay spread associated with the power lines, which are channel parameters that provide important information for determining the data transmission rate and designing appropriate equalization techniques for power line communications (PLC). We start by showing that the key to the RMS delay spread estimation problem is the determination of the channel order, i.e., the effective duration of the channel impulse response. We next discuss various ways to estimate the impulse response length from a noise-corrupted channel estimate. In particular, four different methods, namely a signal energy estimation (SEE) technique, a generalized Akaike information criterion (GAIC) based test, a generalized likelihood ratio test (GLRT), and a modified GLRT, are derived for determining the effective length of a signal contaminated by noise. These methods are compared with one another using both simulated and experimentally measured power line data. The experimental data was collected for power line characterization at frequencies between 1 and 60 MHz.
Starting Page	229
Ending Page	233
File Size	479123
Page Count	5
File Format	PDF
ISBN	0780359887
DOI	10.1109/SSAP.2000.870117
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-08-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Delay estimation Testing Automation Data communication Power line communications Programmable control Delay effects Signal to noise ratio Power measurement Pollution measurement
Content Type	Text
Resource Type	Article

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